CN102571179B - Based on the cross-layer optimizing method for designing of incomplete channel condition information in mimo system - Google Patents

Abstract

The present invention relates to the cross-layer optimizing method for designing based on incomplete channel condition information (CSI) and antenna transmission power division in wireless space-time coding MIMO system, wherein carried power distribution algorithm is optimized to maximize system average spectral efficiency (ase) (ASE) for target.In order to simplify the complexity of optimization problem, according to the relation between system ASE and average packet error rate (PER), this problem is converted into minimization system mean P ER.In order to avoid the successive ignition of existing optimal power allocation algorithm calculates, propose a kind of power distribution method based on maximum compression signal to noise ratio, enclosed power can be obtained and distribute.This algorithm without any need for iterative computation, and can meet positive requirement, and owing to being similar to preferably, can obtain and existing optimal algorithm performance closely, achieves complexity and performance is effectively compromised.Shown by matlab emulation platform, the incomplete CSI that the design of this cross-layer optimizing can effectively utilize feedback carries out rate and power adaptive and automatic repeat request, drastically increases the spectrum efficiency of system.

Description

Based on the cross-layer optimizing method for designing of incomplete channel condition information in mimo system

Technical field

The invention belongs to wireless communication field, relate to the cross-layer optimizing method for designing of radio communication, relate to the cross-layer optimizing method for designing based on incomplete channel condition information (CSI, ChannelStateInformation) and power division in mimo system in particular.

Background technology

At present, wireless communication technology has been widely used in social life each side, and various wireless communication data business presents volatile growth to capacity requirement, especially the wireless access of the Internet and multimedia application are to the growth of information throughput demand, exceed the data rate that prior art is supported, a kind of important technology making data rate be able to effectively to increase is exactly settle multiple antenna at system transmitting terminal and receiving terminal, i.e. multiple-input and multiple-output (MIMO, MultipleInputandMultipleOutput) technology, its core concept is spatial temporal signal processing, technology mainly comprises space diversity and spatial reuse etc.Space diversity is used to overcome the channel fading in wireless transmission, and it utilizes the individual transmission of the multiple repeating signal in multiple antennas implementation space, effectively can improve the reliability of system.Space diversity can be divided into receive diversity and transmit diversity.When the channel fading arriving different reception antenna when transmitting is uncorrelated, by merging the signal that different reception antenna receives, receive diversity can be realized.And for transmit diversity, attract people's attention most with space-time block code (STBC, SpaceTimeBlockCoding) technology again.But existing STBC, based on open loop launch scenario, namely without the need to knowing current channel condition information (CSI, ChannelStateInformation), makes systematic function improve limited.The parameters such as relative with open loop launch scenario is closed loop policy, the CSI self-adaptative adjustment transmission mode that transmitting terminal comes according to receiving terminal feedback, thus optimize the performance of wireless MIMO communication system better.Feature wave-beam shaping (Eigen-BF, Eigen-Beamforming) technology, as one of closed-loop MIMO lift-off technology, the CSI of feedback can be utilized to arrange weights be optimized transmitter, strengthen the desired signal launched, become one of key technology of third generation partner program (3GPP, 3rdGenerationPartnershipProject) LTE.

Simultaneously, in order to adapt to wireless communications environment better, make full use of limited wireless network resource to realize optimal design, there has been proposed cross layer design scheme, its main thought refers to by transmitting specific information between each layer of protocol stack, carrys out the work between each layer of coordinating protocol stack, makes the service quality (QoS conscientiously ensureing multimedia service at wireless communications environment, QualityofService), the structure of cross layer design as shown in Figure 1.As can be seen from accompanying drawing 1, cross layer design is exactly on the basis of traditional layered protocol stack, add a cross layer design module, this module is connected with each layer of protocol stack, store and coordinate the key parameter of each layer, information can be transmitted between each layer of protocol stack, and be no longer be only limited to adjacent two-layer between, all layers integrally design, limited Radio Resource so just can be made to maximize the use, improve the performance of wireless communication system.In numerous cross layer design scheme, the cross layer design of point-to-point, each layer namely more than data link layer, without the need to considering, considers physical layer and this two-layer cross layer design of data link layer for general, as the element of radio communication cross layer design, be subject to paying close attention to greatly and research.In order to improve the spectrum efficiency of wireless communication system, in physical layer, Adaptive Modulation (AM, AdaptiveModulation) technology is proposed, object be allow the rate of information throughput and time the channel that becomes match.But high reliability to be reached in physical layer, modulation rate or code rate will be reduced.The another kind of way improving information transmission reliability is exactly the automatic repeat request (ARQ of entrance link layer, AutomaticRepeatre-Quest) mechanism, receiving terminal is when reception packet is made mistakes, request transmitting terminal is retransmitted, but number of retransmissions increases and will reduce system spectral efficiency.In order to solve the contradiction between the rate of information throughput and reliability, the associating AM of physical layer and the ARQ of link layer is carried out cross layer design.In data link layer, use ARQ can revise accidental mistake bag, this reduces the Wrong control request of physical layer AM, thus use the modulation system of two-forty, reach the object improving system spectral efficiency.

For the feature of wireless communications environment, research mimo system cross layer design becomes hot subject in recent years.A.Maaref and X.F.Lu utilizes STBC to realize the cross layer design of mimo system respectively.W.Chen proposes the cross layer design across physical layer and network layer under complete CSI, gives the optimal power allocation between user and rate-allocation.Certainly, owing to there is evaluated error, in reality, complete CSI cannot be obtained.For this reason, the people such as W.Hassan analyze under incomplete CSI, utilize the Transmit Antenna Selection based on feedback judgement to optimize the cross layer design of the mimo system based on space diversity.Guo Lili is also under incomplete channel estimating, MIMO combine with technique maximum-ratio combing (MRC is proposed, MaximalRatioCombining) closed loop cross layer design scheme, can improve the spectrum efficiency (SE, SpectralEfficiency) of cordless communication network.For CSI feedback incomplete in space-time coding MIMO system, the people such as G.Jongren, by minimizing the upper dividing value of pairwise error probability, obtain optimal power allocation scheme, but need to be solved by a large amount of iterative search, therefore complexity is higher.The people such as S.L.Zhou propose a kind of bayesian criterion by minimizing error sign ratio and carry out optimization system transmitted power, give the suboptimum power allocation scheme based on water filling criterion, but need to judge average signal-to-noise ratio whether in threshold range.The people such as L.Xian then carry out power division optimization by maximizing received signal to noise ratio, and utilize numerical search to obtain corresponding power factor, and analysis result shows the situation being better than constant power distribution based on the systematic function of this power division.

But, do not make full use of power division division in existing research and carry out cross-layer optimizing design, systematic function is improved limited.Therefore, the incomplete CSI situation that the present invention will cause for feedback delay, the cross-layer optimizing method distributed based on transmitting antenna power in design STBC-MIMO system, improves the spectrum efficiency of system with this.Mainly through the relation between the average spectral efficiency (ase) (ASE, AverageSpectralEfficiency) of system and power allocation factor, distribute to the optimization carrying out power to maximize system ASE for target.In order to reduce the computation complexity of optimal solution, adopting a kind of method of maximum compression signal to noise ratio, designing a kind of suboptimum power allocation scheme of low complex degree, can closed solutions be obtained.And have similar performance to optimal power allocation algorithm, thus the inventive method achieves effective compromise of complexity and performance.

Below will be described in detail object of the present invention and characteristic by reference to the accompanying drawings by specific embodiment, these specific embodiments are illustrative, do not have restricted.

Summary of the invention

The present invention be directed to STBC-MIMO system, have studied the cross-layer optimizing method for designing based on incomplete CSI and power division, wherein carried power distribution algorithm is optimized to maximize system ASE for target.The cross-layer optimizing method for designing that the present invention proposes have employed following steps:

(1) when giving the incomplete CSI that feedback delay causes, in conjunction with the cross-layer optimizing design principle figure of power division and feature wave-beam shaping and Mathematical Modeling in mimo system.

The cross-layer optimizing design principle figure of mimo system as shown in Figure 2.

When figure 2 shows incomplete CSI, in conjunction with the cross-layer optimizing design principle figure of power division and feature wave-beam shaping in mimo system.Modulation signal carries out power optimization distribution after STBC coding, then adjusts in conjunction with feature wave-beam shaping the beam direction that transmits, and finally sends from each transmitting antenna; At receiving terminal, obtain CSI by good channel estimating, be used for STBC decoding and adaptive demodulation, feed back to ARQ maker simultaneously and decide number of retransmissions, also need in addition to feed back to transmitting terminal to carry out AM, power division and feature wave-beam shaping.

Consider that a wireless MIMO communication system has N _tsecondary transmitting antenna and N _rsecondary reception antenna, its channel gain matrix N _r× N _tdimension matrix represent, wherein element h _{j, i}be expressed as the channel gain of the secondary reception antenna from the i-th secondary transmitting antenna to jth.At receiving terminal, suppose that the channel matrix that t is estimated is corresponding received signal to noise ratio is then feed back to transmitting terminal with having time delay τ by feedback link, then now the system acceptance signal to noise ratio in (t+ τ moment) is γ, and channel matrix is H, with between relation can be expressed as

$H=\mathrm{\ρ}\hat{H}+E,$ Expression formula 1

Wherein, ρ is the coefficient correlation of the not channel gain in the same time of same distribution, separate with evaluated error E.

Incoming symbol carries out power division and feature wave-beam shaping after STBC coding, and its system input and output formed are closed and are

$Y=\sqrt{P_t}H\hat{U}\mathrm{PX}+N,$ Expression formula 2

Wherein, Y is N _rthe Received signal strength matrix of × T dimension, P _tfrom N _tthe power of secondary transmitting antenna, N _t× N _tdimension unitary matrice for beamforming matrix, by eigenvalues Decomposition obtains, namely corresponding to characteristic value diagonal matrix and descending; X is the N after STBC coding _t× T ties up sign matrix, and symbol energy is normalized to 1; N represents N _rthe additive noise matrix of × T dimension, its element and $P=\mathrm{diag}(\sqrt{P_1},\sqrt{P_2},...,\sqrt{P_{N_t}})$ Be power allocation factor diagonal matrix, it meets

$\underset{i=1}{\overset{N_t}{\mathrm{\Σ}}}{P}_i=1,$ Expression formula 3

P _i≥0，i＝1，...，N _t。Expression formula 4

So, according to expression formula 2, the instantaneous received signal to noise ratio γ of system is

$\mathrm{\γ}=\frac{P_t}{R_c{\mathrm{\σ}}_n^2}{\left|\right|\tilde{H}P\left|\right|}_F^2=\frac{P_t}{R_c{\mathrm{\σ}}_n^2}\underset{i=1}{\overset{N_t}{\mathrm{\Σ}}}{P}_i{\mathrm{\β}}_i,$ Expression formula 5

Wherein, r _cfor STBC code check, ${\mathrm{\β}}_i=\underset{j=1}{\overset{N_r}{\mathrm{\Σ}}}{\left|\underset{k=1}{\overset{N_t}{\mathrm{\Σ}}}{h}_{j,k}{\hat{u}}_{k,i}\right|}^2.$

(2) corresponding power optimization targets is derived according to the system model of described step (1).

Analyzed from described step (1), the PDF of system acceptance signal to noise ratio γ is not easy to obtain, therefore cannot the ASE of solving system according to this, also the closed expression of ASE just directly can not be utilized to be optimized and to obtain power allocation scheme, need problem to carry out equivalence to transform, the inventive method utilizes the correlations such as the ASE of system and mean P ER to transform optimization aim.

First, according to the average spectral efficiency (ase) of system with the spectrum efficiency of physical layer average transmission number of times and average packet error rate the relation each other such as (PER, PacketErrorRate), the average spectral efficiency (ase) obtaining system is

$\stackrel{\‾}{\mathrm{Se}}={\stackrel{\‾}{\mathrm{Se}}}_{\mathrm{phy}}/\stackrel{\‾}{N}={\stackrel{\‾}{\mathrm{Se}}}_{\mathrm{phy}}\·(1-\stackrel{\‾}{\mathrm{Per}})/(1-{\stackrel{\‾}{\mathrm{Per}}}^{N_r^{\max }+1}).$ Expression formula 6

Wherein, for maximum retransmission.

Consider less (far below 1), can be by with to be closely seemingly expressed as

$\stackrel{\‾}{\mathrm{Se}}\≈(1-\stackrel{\‾}{\mathrm{Per}})\·{\stackrel{\‾}{\mathrm{Se}}}_{\mathrm{phy}}=\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{R}_n\·[{\∫}_{{\mathrm{\γ}}_n}^{{\mathrm{\γ}}_{n+1}}(1-{\widetilde{\mathrm{Per}}}_n)\·p_{\widehat{\mathrm{\γ}}}\left(\widehat{\mathrm{\γ}}\right)d\widehat{\mathrm{\γ}}],$ Expression formula 7

Wherein, N is modulation system sum, R _nrepresent the information rate in conjunction with modulation rate and STBC code check, γ _ncorresponding to the threshold value of modulation system n, represent the instantaneous PER based on expired CSI when adopting modulation system n, for probability density function.From expression formula 7, maximization system ASE is equivalent to and minimizes wherein can utilize known about the conditional probability density function of H obtains under condition, that is:

${\widetilde{\mathrm{Per}}}_n={\∫\mathrm{Per}}_n\left(\tilde{H}\right|\hat{H}){\mathrm{\ρ}}_{\mathrm{\β}|\hat{H}}\left(\mathrm{\β}\right|\hat{H})\mathrm{d\β}.$ Expression formula 8

Wherein: based on condition PDF.Thus power optimization problem is just converted under the condition meeting expression formula 3 and expression formula 4, minimizes obtain corresponding optimizing power distribution factor, namely utilize Lagrange multiplier method to provide optimization aim to be

$F\left(P_i\right)={\widetilde{\mathrm{Per}}}_n+\mathrm{\λ}(\underset{i=1}{\overset{N_t}{\mathrm{\Σ}}}{P}_i-1).$ Expression formula 9

Wherein, F (P _i) be about P _itarget function, λ is Lagrange multiplier.

(3) according to the power optimization targets function that expression formula 9 in described step (2) provides, and the method for compression signal to noise ratio is utilized to solve corresponding enclosed power distribution factor.

To the P of expression formula 9 _iask partial derivative, namely p can be obtained _ithe closed expression about λ, also need the power constraints provided according to expression formula 3 and expression formula 4 to carry out iterative search, this kind of alternative manner is referred to as JSO method.

The present invention based on incomplete CSI, will utilize feature wave-beam shaping, propose the method adopting compression signal to noise ratio, expression formula 9 be solved the rear problem of iterative search λ that needs and transform, the final closed solutions obtaining power allocation factor.

As the known complete CSI of transmitting terminal, feature wave-beam shaping only need choose maximum characteristic value characteristic of correspondence vector, effective received signal to noise ratio of system just can be made maximum, and feature wave-beam shaping now is just equivalent to one-dimensional wave beam shaping (1-Dbeamforming), i.e. P ₁=1, P _i=0, i=2 ..., N _t.But for incomplete CSI, one-dimensional characteristic beam forming power distribution algorithm can not make received signal to noise ratio maximum, in order to reduce the impact of incomplete CSI on received signal to noise ratio, the compression received signal to noise ratio γ utilizing seminar to propose _αbe optimized, be expressed as

${\mathrm{\γ}}_{\mathrm{\α}}=\frac{P_t}{R_c{\mathrm{\σ}}_n^2}\underset{i=1}{\overset{N_t}{\mathrm{\Σ}}}{\left(P_i{\widehat{\stackrel{\‾}{\mathrm{\β}}}}_i\right)}^{\mathrm{\α}},$ Expression formula 10

Wherein, represent based on β _iconditional mean; α is compressibility factor, can optimize γ by adjustment α _α.Expression formula 10 is to de-emphasize most high-amplitude wave bundle, but suitably introduces other each wave beams, thus reduces the impact of incomplete CSI on most high-amplitude wave bundle.Thus, each wave beam can be combined to adjust received signal to noise ratio, and then improve systematic function.

Under the condition of expression formula 3, maximize the γ shown in expression formula 10 _αobtain P _i.Here first do not consider the condition of expression formula 4, remove the constant term of expression formula 10, establishing target function is simultaneously

$F=\underset{i=1}{\overset{N_t}{\mathrm{\Σ}}}{\left(P_i{\widehat{\stackrel{\‾}{\mathrm{\β}}}}_i\right)}^{\mathrm{\α}}+\mathrm{\η}(\underset{i=1}{\overset{N_t}{\mathrm{\Σ}}}{P}_i-1),$ Expression formula 11

Wherein, η is Lagrange multiplier.

By the P to expression formula 11 _iask partial derivative, namely can obtain

$P_i={\left(\frac{\mathrm{\η}}{\mathrm{\α}}\right)}^{\frac{1}{\mathrm{\α}-1}}{\widehat{\stackrel{\‾}{\mathrm{\β}}}}_i^{-\frac{\mathrm{\α}}{\mathrm{\α}-1}},i=1,...,N_t.$ Expression formula 12

Utilize expression formula 3, can P be obtained _iabout the function of independent variable μ

$P_i=\frac{{\widehat{\stackrel{\‾}{\mathrm{\β}}}}_i^{\mathrm{\μ}}}{\underset{i=1}{\overset{N_t}{\mathrm{\Σ}}}{\widehat{\stackrel{\‾}{\mathrm{\β}}}}_i^{\mathrm{\μ}}},i=1,...,N_t.$ Expression formula 13

Wherein, due to 0 < α < 1, so μ > 0; By expression formula 13 also known P _i> 0 meets the condition of expression formula 4 automatically, and avoid existing document needs iteration to judge P in solving _ithe process of > 0.

By the P that expression formula 13 represents _ifunction about μ is updated to expression formula 8, the function L (μ) about μ can be expressed as, but be difficult to direct solution and go out μ, therefore need to simplify L (μ), namely at μ=0 place, Taylor series expansion is adopted to L (μ), and ignore the every of more than 2 items, shown in it is unfolded as follows:

$L\left(\mathrm{\&mu;}\right)\&cong;L\left(0\right)+L^{\&prime;}\left(0\right)\mathrm{\&mu;}+L^{\&prime;\&prime;}\left(0\right){\mathrm{\&mu;}}^2.$ Expression formula 14

By asking local derviation and be placed in 0 to expression formula (14) can μ be obtained to μ, and substitute into expression formula 13, obtain enclosed power and distribute, reduce the complexity of calculating, approach with optimum iterative power allocation algorithm simultaneously, achieve effective compromise of complexity and performance.Particularly adopt the cross-layer design method of this power allocation scheme, the average SE of system can be made to be greatly improved.

Below in conjunction with drawings and Examples, the present invention is further illustrated.

Accompanying drawing explanation

Fig. 1 is the structural representation of cross layer design.

Fig. 2 is system schematic diagram of the present invention.

Fig. 3 is different average spectral efficiency (ase) (the normalization feedback delay f of lower 21 receipts antenna systems _dτ=0.05).

Fig. 4 is different f _dthe average spectral efficiency (ase) of lower 2 the 1 receipts antenna systems of τ

Embodiment

The cross-layer optimizing design that the present invention proposes is verified by Matlab platform.Can find out that the program effectively can improve the spectrum efficiency of system from simulation result.Provide the concrete technical scheme implemented below:

(1) system works is in Flat quasistatic rayleigh fading channel, then h _{j, i}obey Rayleigh independent same distribution, i.e. h _{j, i}~ CN (0,1), and and the element ε of E _{j, i}all independent identically distributed multiple gaussian variable, i.e. ε _{j, i}~ CN (0,1-| ρ | ²).

By H in expression formula 1 and relation known, under known condition, element obey independent of answering Gaussian Profile, its average is variance is σ ²=1-| ρ | ².Can obtain thus: relevant β _ibased on conditional probability density function (PDF, ProbabilityDensityFunction) be

$p_{{\mathrm{\&beta;}}_i|\hat{H}}\left({\mathrm{\&beta;}}_i\right|\hat{H})=\frac{1}{{\mathrm{\&sigma;}}^2}{\left(\frac{{\mathrm{\&beta;}}_i}{{\widetilde{\mathrm{\&beta;}}}_i}\right)}^{\frac{N_r-1}{2}}\exp (-\frac{{\widetilde{\mathrm{\&beta;}}}_i+{\mathrm{\&beta;}}_i}{{\mathrm{\&sigma;}}^2})\&CenterDot;I_{N_r-1}\left(\frac{2\sqrt{{\widetilde{\mathrm{\&beta;}}}_i{\mathrm{\&beta;}}_i}}{{\mathrm{\&sigma;}}^2}\right),$ Expression formula 15

Wherein, ${\widetilde{\mathrm{\&beta;}}}_i=\underset{j=1}{\overset{N_r}{\mathrm{\&Sigma;}}}{\left|\mathrm{\&rho;}\underset{k=1}{\overset{N_t}{\mathrm{\&Sigma;}}}{\hat{h}}_{j,k}{\hat{u}}_{k,i}\right|}^2={\mathrm{\&rho;}}^2\&CenterDot;\underset{j=1}{\overset{N_r}{\mathrm{\&Sigma;}}}{\left|\underset{k=1}{\overset{N_t}{\mathrm{\&Sigma;}}}{\hat{h}}_{j,k}{\hat{u}}_{k,i}\right|}^2={\mathrm{\&rho;}}^2\&CenterDot;{\widehat{\mathrm{\&lambda;}}}_i.$

(2) in systems in which, the modulation system that AM adopts is multilevel quadrature amplitude modulation(PAM) (M-QAM, Multi-levelQuadratureAmplitudeModulation) mode, its approximate PER under additive white Gaussian noise (AWGN, AdditiveWhiteGaussianNoise) channel is

${\mathrm{Per}}_n\left(\mathrm{\&gamma;}\right)\&ap;\left\{\begin{array}{cc}1,& \mathrm{\&gamma;}<{\mathrm{\&gamma;}}_{\mathrm{pn}}\\ a_n\exp (-g_n\mathrm{\&gamma;}),& \mathrm{\&gamma;}\&GreaterEqual;{\mathrm{\&gamma;}}_{\mathrm{pn}}\end{array}\right..$ Expression formula 16

In conjunction with expression formula 5, the approximate PER based on incomplete CSI and power division is

${\mathrm{Per}}_n\left(\tilde{H}\right|\hat{H})\&ap;a_n\exp (-{\mathrm{\&zeta;}}_n\underset{i=1}{\overset{N_t}{\mathrm{\&Sigma;}}}{P}_i{\mathrm{\&beta;}}_i),$ Expression formula 17

Wherein, for the ease of analyzing, simplify threshold value γ here _pnimpact.

Utilize expression formula 15 and 17, by expression formula (8) can calculate based on average instantaneous PER,

${\widetilde{\mathrm{Per}}}_n=a_n\underset{i=1}{\overset{N_t}{\mathrm{\&Pi;}}}\frac{1}{{(1+{\mathrm{\&zeta;}}_n{\mathrm{\&sigma;}}^2{P}_i)}^{N_r}}\exp (-\frac{{\mathrm{\&zeta;}}_n{\widetilde{\mathrm{\&beta;}}}_i{P}_i}{1+{\mathrm{\&zeta;}}_n{\mathrm{\&sigma;}}^2{P}_i}).$ Expression formula 18

By minimizing shown in expression formula 18 corresponding optimizing power distribution factor P can be tried to achieve _i; For the ease of solving, taken the logarithm, namely

$L\left(P_i\right)=\ln \left(\frac{{\widetilde{\mathrm{Per}}}_n}{a_n}\right)=-\underset{i=1}{\overset{N_t}{\mathrm{\&Sigma;}}}[N_r\ln (1+{\mathrm{\&zeta;}}_n{\mathrm{\&sigma;}}^2{P}_i)+\frac{{\mathrm{\&zeta;}}_n{\widetilde{\mathrm{\&beta;}}}_i{P}_i}{1+{\mathrm{\&zeta;}}_n{\mathrm{\&sigma;}}^2{P}_i}].$ Expression formula 19

(3) expression formula 14 is updated in expression formula 19, then expression formula 19 is expressed as L (μ), and adopts Taylor series expansion at μ=0 place, ignores the every of more than 2 items simultaneously, and then the form of expression formula 14 can be expressed as, its each term coefficient is

$L\left(0\right)=L\left(\mathrm{\&mu;}\right){|}_{\mathrm{\&mu;}=0}=-[N_t{N}_r\ln \left(\frac{N_t+{\mathrm{\&zeta;}}_n{\mathrm{\&sigma;}}^2}{N_t}\right)+\frac{{\mathrm{\&zeta;}}_n}{N_t+{\mathrm{\&zeta;}}_n{\mathrm{\&sigma;}}^2}\underset{i=1}{\overset{N_t}{\mathrm{\&Sigma;}}}{\widetilde{\mathrm{\&beta;}}}_i];$ Expression formula 20

$L^{\&prime;}\left(0\right)=\frac{N_t{\mathrm{\&zeta;}}_n}{{(N_t+{\mathrm{\&zeta;}}_n{\mathrm{\&sigma;}}^2)}^2}\underset{i=1}{\overset{N_t}{\mathrm{\&Sigma;}}}{\widetilde{\mathrm{\&beta;}}}_i{b}_i,$ Expression formula 21

$L^{\&prime;\&prime;}\left(0\right)=\frac{N_r{\mathrm{\&zeta;}}_n^2{\mathrm{\&sigma;}}^4}{{(N_t+{\mathrm{\&zeta;}}_n{\mathrm{\&sigma;}}^2)}^2}\underset{i=1}{\overset{N_t}{\mathrm{\&Sigma;}}}{b}_i^2+\frac{{2N}_t{\mathrm{\&zeta;}}_n^2{\mathrm{\&sigma;}}^2}{{(N_t+{\mathrm{\&zeta;}}_n{\mathrm{\&sigma;}}^2)}^3}\underset{i=1}{\overset{N_t}{\mathrm{\&Sigma;}}}{\widetilde{\mathrm{\&beta;}}}_i{b}_i^2.$ Expression formula 22

Wherein, and meet by L (0) < 0 of expression formula 20, " (0) > 0 can find out L ' (0) > 0 of the expression formula 21 and L of expression formula 22; L (μ) is the convex function about μ, therefore there is solution as follows

$\mathrm{\&mu;}=\frac{N_t\underset{i=1}{\overset{N_t}{\mathrm{\&Sigma;}}}{\widetilde{\mathrm{\&beta;}}}_i{b}_i}{N_r{\mathrm{\&zeta;}}_n{\mathrm{\&sigma;}}^4\underset{i=1}{\overset{N_t}{\mathrm{\&Sigma;}}}{b}_i^2+(2N_t{\mathrm{\&zeta;}}_n{\mathrm{\&sigma;}}^2/(N_t+{\mathrm{\&zeta;}}_n{\mathrm{\&sigma;}}^2))\underset{i=1}{\overset{N_t}{\mathrm{\&Sigma;}}}{\widetilde{\mathrm{\&beta;}}}_i{b}_i^2}.$ Expression formula 23

Finally expression formula 23 is substituted into expression formula 13, the power allocation factor of enclosed can be obtained, effectively simplify iterative search and the judgement of JSO power distribution algorithm.

The present invention proposes the cross-layer optimizing method for designing based on incomplete CSI and power division in a kind of mimo system, accompanying drawing 3 and fig. 4 shows the analysis of this method in spectrum efficiency.(STBC of employing is G to fig. 3 gives 21 receipts ₂code) cross layer design of antenna system is in different maximum retransmission under ASE, and the system ASE under different capacity allocation algorithm to be compared, wherein normalization feedback delay f _dτ=0.05.As can be seen from accompanying drawing 3, compared to the system based on constant power (Equalpower) allocation algorithm, identical the system ASE of lower the present invention program can be increased to 0.8bts/s/Hz, embodies the advantage of the inventive method; Simultaneously almost consistent with the ASE based on JSO iteration optimal power allocation algorithm, demonstrate the validity of the inventive method, and its complexity is much lower.Fig. 4 shows different f _dthe ASE of lower 2 the 1 receipts antenna system cross layer design of τ, wherein and compare the system ASE of application power algorithm of the present invention, Equalpower and one-dimensional characteristic beam forming (1-Dbeamforming) power distribution algorithm.As seen from the figure, the increase of time delay can cause the reduction of system ASE.Work as f _dduring τ=0.01, the inventive method is consistent with the ASE under 1-Dbeamforming power distribution algorithm, all be better than the system ASE based on Equalpower algorithm, illustrate that the CSI now obtained is close to complete, time delay does not affect it, and under this just demonstrates complete CSI, 1-Dbeamforming is optimal power allocation scheme; And as the comparatively large (f of time delay _dτ=0.1) time, time lower, the ASE of 1-Dbeamforming and the present invention program is close, and be all better than Equalpower, and along with the rising of signal to noise ratio, ASE under 1-Dbeamforming will be inferior to the present invention program, and the ASE under Equalpower moves closer in the present invention program, just demonstrate the proposed optimizing power allocation algorithm based on incomplete CSI and trend towards 1-Dbeamforming at low signal-to-noise ratio, criterion when high s/n ratio again close to Equalpower, also just demonstrates the feasibility of the present invention program.

This shows, the superiority of side's scheme of the present invention, it is consistent with the systematic function based on optimal power allocation algorithm, but avoids the iterative computation of optimal power algorithm, efficiently reduce amount of calculation, achieve effective compromise of complexity and systematic function.

The content be not described in detail in the present patent application book belongs to the known prior art of professional and technical personnel in the field.

Claims (1)

1. Based on the cross-layer optimizing method for designing of incomplete channel condition information CSI in 1.MIMO system, it is characterized in that comprising step as follows:

   (1) based on the incomplete channel condition information that feedback delay causes, modulation signal carry out after the Adaptive Modulation AM and space-time block code of physical layer power optimization distribution, again in conjunction with feature wave-beam shaping to adjust transmit beam direction, then send from each transmitting antenna; At receiving terminal, obtain CSI by good channel estimating, for block decoding during sky and adaptive demodulation, feed back CSI simultaneously and decide number of retransmissions to the HARQ ARQ maker of data link layer;

   (2) the instantaneous received signal to noise ratio γ of the system that solves, provides optimization aim and namely maximizes system average spectral efficiency (ase) ASE;

   (3) maximization system average spectral efficiency (ase) is equivalent to and minimizes instantaneous Packet Error Ratio power optimization problem is just converted under the constraints that transmitting power is certain, minimizes

   (4) utilization minimizes be equivalent to the principle maximizing signal to noise ratio, maximum compression signal to noise ratio γ under the constraints that transmitting power is certain _α, utilize method of Lagrange multipliers to obtain power partition coefficient P _iwith compressibility factor α, the relational expression of 0 < α < 1, and then be expressed as function;

   (5) by power partition coefficient P _ibe updated to instantaneous Packet Error Ratio then can be expressed as the function L (μ) about μ, and then problem is converted into the μ asking and make L (μ) minimum; At μ=0 place, Taylor series expansion is carried out to L (μ), and ignores the every of more than 2 items, ask its extreme point and obtain, namely utilizing the L (μ) of expansion, ask time corresponding μ value;

   (6) the μ value obtained is substituted into P _iabout in the function of μ, the power allocation factor of enclosed can be obtained.